{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 一、读写文本格式数据"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "pandas提供了一些用于将表格型数据读取为DataFrame对象的函数。下面表格对其做了总结，其中read_csv和read_table可能会是你今后用得最多的。"
   ]
  },
  {
   "attachments": {
    "image.png": {
     "image/png": "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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![image.png](attachment:image.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "***"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "#导包\n",
    "import numpy as np\n",
    "import pandas as pd \n",
    "import matplotlib as plt\n",
    "np.random.seed(12345)\n",
    "plt.rc('figure',figsize=(10,6))\n",
    "np.set_printoptions(precision=4,suppress=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## read_csv()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "a,b,c,d,message\n",
      "1,2,3,4,hello\n",
      "5,6,7,8,world\n",
      "9,10,11,12,foo\n"
     ]
    }
   ],
   "source": [
    "#（1）\n",
    "#将原始内容打印在屏幕上\n",
    "!type \"examples\\ex1.csv\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>a</th>\n",
       "      <th>b</th>\n",
       "      <th>c</th>\n",
       "      <th>d</th>\n",
       "      <th>message</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>hello</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>7</td>\n",
       "      <td>8</td>\n",
       "      <td>world</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>9</td>\n",
       "      <td>10</td>\n",
       "      <td>11</td>\n",
       "      <td>12</td>\n",
       "      <td>foo</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   a   b   c   d message\n",
       "0  1   2   3   4   hello\n",
       "1  5   6   7   8   world\n",
       "2  9  10  11  12     foo"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#read_csv()\n",
    "df=pd.read_csv('examples/ex1.csv')\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "*** "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1,2,3,4,hello\n",
      "5,6,7,8,world\n",
      "9,10,11,12,foo\n"
     ]
    }
   ],
   "source": [
    "#（2）\n",
    "#打印ex2.csv原始内容\n",
    "!type \"examples\\ex2.csv\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>hello</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>7</td>\n",
       "      <td>8</td>\n",
       "      <td>world</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>9</td>\n",
       "      <td>10</td>\n",
       "      <td>11</td>\n",
       "      <td>12</td>\n",
       "      <td>foo</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   0   1   2   3      4\n",
       "0  1   2   3   4  hello\n",
       "1  5   6   7   8  world\n",
       "2  9  10  11  12    foo"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#若文件没有标题行，则可以让pandas为其分配默认的列名\n",
    "pd.read_csv('examples/ex2.csv', header=None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>a</th>\n",
       "      <th>b</th>\n",
       "      <th>c</th>\n",
       "      <th>d</th>\n",
       "      <th>message</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>hello</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>7</td>\n",
       "      <td>8</td>\n",
       "      <td>world</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>9</td>\n",
       "      <td>10</td>\n",
       "      <td>11</td>\n",
       "      <td>12</td>\n",
       "      <td>foo</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   a   b   c   d message\n",
       "0  1   2   3   4   hello\n",
       "1  5   6   7   8   world\n",
       "2  9  10  11  12     foo"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#也可以自己定义列名\n",
    "pd.read_csv('examples/ex2.csv', names=['a', 'b', 'c', 'd', 'message'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "***"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>a</th>\n",
       "      <th>b</th>\n",
       "      <th>c</th>\n",
       "      <th>d</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>message</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>hello</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>world</th>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>7</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>foo</th>\n",
       "      <td>9</td>\n",
       "      <td>10</td>\n",
       "      <td>11</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         a   b   c   d\n",
       "message               \n",
       "hello    1   2   3   4\n",
       "world    5   6   7   8\n",
       "foo      9  10  11  12"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#(3)\n",
    "#若要将某列指定为index，则可通过index_col参数指定“message”\n",
    "names=['a', 'b', 'c', 'd', 'message']\n",
    "pd.read_csv('examples/ex2.csv', names=names, index_col='message')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "key1,key2,value1,value2\n",
      "one,a,1,2\n",
      "one,b,3,4\n",
      "one,c,5,6\n",
      "one,d,7,8\n",
      "two,a,9,10\n",
      "two,b,11,12\n",
      "two,c,13,14\n",
      "two,d,15,16\n"
     ]
    }
   ],
   "source": [
    "#也可以指定多个列，形成层次化索引\n",
    "!type \"examples\\csv_mindex.csv\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>value1</th>\n",
       "      <th>value2</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>key1</th>\n",
       "      <th>key2</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">one</th>\n",
       "      <th>a</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>b</th>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>c</th>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>d</th>\n",
       "      <td>7</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">two</th>\n",
       "      <th>a</th>\n",
       "      <td>9</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>b</th>\n",
       "      <td>11</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>c</th>\n",
       "      <td>13</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>d</th>\n",
       "      <td>15</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           value1  value2\n",
       "key1 key2                \n",
       "one  a          1       2\n",
       "     b          3       4\n",
       "     c          5       6\n",
       "     d          7       8\n",
       "two  a          9      10\n",
       "     b         11      12\n",
       "     c         13      14\n",
       "     d         15      16"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.read_csv('examples/csv_mindex.csv',index_col=['key1','key2'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "***"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "# hey!\n",
      "a,b,c,d,message\n",
      "# just wanted to make things more difficult for you\n",
      "# who reads CSV files with computers, anyway?\n",
      "1,2,3,4,hello\n",
      "5,6,7,8,world\n",
      "9,10,11,12,foo\n"
     ]
    }
   ],
   "source": [
    "#(4)\n",
    "#处理异形文件，比如跳过某些行\n",
    "!type \"examples\\ex4.csv\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>a</th>\n",
       "      <th>b</th>\n",
       "      <th>c</th>\n",
       "      <th>d</th>\n",
       "      <th>message</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>hello</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>7</td>\n",
       "      <td>8</td>\n",
       "      <td>world</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>9</td>\n",
       "      <td>10</td>\n",
       "      <td>11</td>\n",
       "      <td>12</td>\n",
       "      <td>foo</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   a   b   c   d message\n",
       "0  1   2   3   4   hello\n",
       "1  5   6   7   8   world\n",
       "2  9  10  11  12     foo"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#用skiprows跳过文件的第一行、第三行和第四行\n",
    "pd.read_csv('examples/ex4.csv', skiprows=[0, 2, 3])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "***"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## read_table()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>a</th>\n",
       "      <th>b</th>\n",
       "      <th>c</th>\n",
       "      <th>d</th>\n",
       "      <th>message</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>hello</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>7</td>\n",
       "      <td>8</td>\n",
       "      <td>world</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>9</td>\n",
       "      <td>10</td>\n",
       "      <td>11</td>\n",
       "      <td>12</td>\n",
       "      <td>foo</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   a   b   c   d message\n",
       "0  1   2   3   4   hello\n",
       "1  5   6   7   8   world\n",
       "2  9  10  11  12     foo"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#(1)\n",
    "#read_table()\n",
    "#注意要指定分隔符\n",
    "pd.read_table('examples/ex1.csv',sep=',')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "***"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "            A         B         C\n",
      "aaa -0.264438 -1.026059 -0.619500\n",
      "bbb  0.927272  0.302904 -0.032399\n",
      "ccc -0.264273 -0.386314 -0.217601\n",
      "ddd -0.871858 -0.348382  1.100491\n"
     ]
    }
   ],
   "source": [
    "#(2)\n",
    "#表格可能不是用固定的分隔符去分隔字段的（比如空白符或其它模式）\n",
    "!type \"examples\\ex3.txt\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>A</th>\n",
       "      <th>B</th>\n",
       "      <th>C</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>aaa</th>\n",
       "      <td>-0.264438</td>\n",
       "      <td>-1.026059</td>\n",
       "      <td>-0.619500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bbb</th>\n",
       "      <td>0.927272</td>\n",
       "      <td>0.302904</td>\n",
       "      <td>-0.032399</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ccc</th>\n",
       "      <td>-0.264273</td>\n",
       "      <td>-0.386314</td>\n",
       "      <td>-0.217601</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ddd</th>\n",
       "      <td>-0.871858</td>\n",
       "      <td>-0.348382</td>\n",
       "      <td>1.100491</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            A         B         C\n",
       "aaa -0.264438 -1.026059 -0.619500\n",
       "bbb  0.927272  0.302904 -0.032399\n",
       "ccc -0.264273 -0.386314 -0.217601\n",
       "ddd -0.871858 -0.348382  1.100491"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#空白字符间隔开的,用正则表达式表达为\\s+\n",
    "pd.read_table('examples/ex3.txt', sep='\\s+')\n",
    "#由于列名比数据行的数量少，所以read_table推断第一列应该是DataFrame的索引index"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "***"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## read_csv和read_table常用的选项"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- path:表示文件系统位置，URL，文件型对象的字符串；\n",
    "- sep和delimiter:用于对行中各字段进行拆分的字符序列或正则表达式；\n",
    "- header：用作列名的行号。默认0（第一行），如果没有header行就设置为None；\n",
    "- index_col:用作行索引的列编号或列名。可以是单个名称/数字或多个名称/数字组成的列表(层次化索引)；\n",
    "- names：用于结果的列名列表，结合header=None；\n",
    "- skiprows:需要忽略的行数(从文件开始处算起)，或需要跳过的行号列表(从0开始)；\n",
    "- na_values:一组用于替换NA的值；\n",
    "- comment:用于将注释信息从行尾拆分出去的字符(一个或多个);\n",
    "- parse_dates:尝试将数据解析为日期，默认为False；\n",
    "- keep_date_col:如果连接多列解析日期，则保持参与连接的列。默认为False。\n",
    "- converters：由列号/列名跟函数之间的映射关系组成的字典。例如，{'foo':f}会对foo列的所有值应用函数f；\n",
    "- dayfirst：当解析有歧义的日期时，将其看做国际格式。默认为False；\n",
    "- date_parser:用于解析日期的函数；\n",
    "- nrows：需要读取的行数(从文件开始处算起)；\n",
    "- iterator:返回一个TextParser以便逐块读取文件；\n",
    "- chunksize：文件块的大小(用于迭代)；\n",
    "- skip_footer:需要忽略的行数(从文件末尾处算起)；\n",
    "- verbose:打印各种解析器输出信息，比如“非数值列中缺失值的数量”等；\n",
    "- encoding：用于unicode的文件编码格式；\n",
    "- squeeze：如果数据经解析后仅含一列，则返回Series；\n",
    "- thousands：千分位分隔符，如“，”或“.”；"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "***"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 二、逐块读取文本文件==》nrows"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "在处理很大的文件时，或找出大文件中的参数集以便于后续处理时，你可能只想读取文件的一小部分或逐块对文件进行迭代。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>one</th>\n",
       "      <th>two</th>\n",
       "      <th>three</th>\n",
       "      <th>four</th>\n",
       "      <th>key</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.467976</td>\n",
       "      <td>-0.038649</td>\n",
       "      <td>-0.295344</td>\n",
       "      <td>-1.824726</td>\n",
       "      <td>L</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>-0.358893</td>\n",
       "      <td>1.404453</td>\n",
       "      <td>0.704965</td>\n",
       "      <td>-0.200638</td>\n",
       "      <td>B</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>-0.501840</td>\n",
       "      <td>0.659254</td>\n",
       "      <td>-0.421691</td>\n",
       "      <td>-0.057688</td>\n",
       "      <td>G</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.204886</td>\n",
       "      <td>1.074134</td>\n",
       "      <td>1.388361</td>\n",
       "      <td>-0.982404</td>\n",
       "      <td>R</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.354628</td>\n",
       "      <td>-0.133116</td>\n",
       "      <td>0.283763</td>\n",
       "      <td>-0.837063</td>\n",
       "      <td>Q</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9995</th>\n",
       "      <td>2.311896</td>\n",
       "      <td>-0.417070</td>\n",
       "      <td>-1.409599</td>\n",
       "      <td>-0.515821</td>\n",
       "      <td>L</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9996</th>\n",
       "      <td>-0.479893</td>\n",
       "      <td>-0.650419</td>\n",
       "      <td>0.745152</td>\n",
       "      <td>-0.646038</td>\n",
       "      <td>E</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9997</th>\n",
       "      <td>0.523331</td>\n",
       "      <td>0.787112</td>\n",
       "      <td>0.486066</td>\n",
       "      <td>1.093156</td>\n",
       "      <td>K</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9998</th>\n",
       "      <td>-0.362559</td>\n",
       "      <td>0.598894</td>\n",
       "      <td>-1.843201</td>\n",
       "      <td>0.887292</td>\n",
       "      <td>G</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9999</th>\n",
       "      <td>-0.096376</td>\n",
       "      <td>-1.012999</td>\n",
       "      <td>-0.657431</td>\n",
       "      <td>-0.573315</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>10000 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           one       two     three      four key\n",
       "0     0.467976 -0.038649 -0.295344 -1.824726   L\n",
       "1    -0.358893  1.404453  0.704965 -0.200638   B\n",
       "2    -0.501840  0.659254 -0.421691 -0.057688   G\n",
       "3     0.204886  1.074134  1.388361 -0.982404   R\n",
       "4     0.354628 -0.133116  0.283763 -0.837063   Q\n",
       "...        ...       ...       ...       ...  ..\n",
       "9995  2.311896 -0.417070 -1.409599 -0.515821   L\n",
       "9996 -0.479893 -0.650419  0.745152 -0.646038   E\n",
       "9997  0.523331  0.787112  0.486066  1.093156   K\n",
       "9998 -0.362559  0.598894 -1.843201  0.887292   G\n",
       "9999 -0.096376 -1.012999 -0.657431 -0.573315   0\n",
       "\n",
       "[10000 rows x 5 columns]"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#文本数据很大\n",
    "result=pd.read_csv('examples/ex6.csv')\n",
    "result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>one</th>\n",
       "      <th>two</th>\n",
       "      <th>three</th>\n",
       "      <th>four</th>\n",
       "      <th>key</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.467976</td>\n",
       "      <td>-0.038649</td>\n",
       "      <td>-0.295344</td>\n",
       "      <td>-1.824726</td>\n",
       "      <td>L</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>-0.358893</td>\n",
       "      <td>1.404453</td>\n",
       "      <td>0.704965</td>\n",
       "      <td>-0.200638</td>\n",
       "      <td>B</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>-0.501840</td>\n",
       "      <td>0.659254</td>\n",
       "      <td>-0.421691</td>\n",
       "      <td>-0.057688</td>\n",
       "      <td>G</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.204886</td>\n",
       "      <td>1.074134</td>\n",
       "      <td>1.388361</td>\n",
       "      <td>-0.982404</td>\n",
       "      <td>R</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.354628</td>\n",
       "      <td>-0.133116</td>\n",
       "      <td>0.283763</td>\n",
       "      <td>-0.837063</td>\n",
       "      <td>Q</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        one       two     three      four key\n",
       "0  0.467976 -0.038649 -0.295344 -1.824726   L\n",
       "1 -0.358893  1.404453  0.704965 -0.200638   B\n",
       "2 -0.501840  0.659254 -0.421691 -0.057688   G\n",
       "3  0.204886  1.074134  1.388361 -0.982404   R\n",
       "4  0.354628 -0.133116  0.283763 -0.837063   Q"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#通过nrows进行指定，读取几行\n",
    "pd.read_csv('examples/ex6.csv',nrows=5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "***"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 三、将数据写出到文本格式==》to_csv()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>something</th>\n",
       "      <th>a</th>\n",
       "      <th>b</th>\n",
       "      <th>c</th>\n",
       "      <th>d</th>\n",
       "      <th>message</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>one</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>3.0</td>\n",
       "      <td>4</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>two</td>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>NaN</td>\n",
       "      <td>8</td>\n",
       "      <td>world</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>three</td>\n",
       "      <td>9</td>\n",
       "      <td>10</td>\n",
       "      <td>11.0</td>\n",
       "      <td>12</td>\n",
       "      <td>foo</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  something  a   b     c   d message\n",
       "0       one  1   2   3.0   4     NaN\n",
       "1       two  5   6   NaN   8   world\n",
       "2     three  9  10  11.0  12     foo"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#读取一个文件\n",
    "data=pd.read_csv('examples/ex5.csv')\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "#（1）\n",
    "#利用DataFrame的to_csv方法，我们可以将数据写到一个以逗号分隔的文件中\n",
    "data.to_csv('examples/out.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      ",something,a,b,c,d,message\n",
      "0,one,1,2,3.0,4,\n",
      "1,two,5,6,,8,world\n",
      "2,three,9,10,11.0,12,foo\n"
     ]
    }
   ],
   "source": [
    "!type \"examples\\out.csv\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "|something|a|b|c|d|message\r\n",
      "0|one|1|2|3.0|4|\r\n",
      "1|two|5|6||8|world\r\n",
      "2|three|9|10|11.0|12|foo\r\n"
     ]
    }
   ],
   "source": [
    "#（2）\n",
    "#还可以指定其他的分隔符，用sep属性来指定\n",
    "#这里直接写出到sys.stdout，所以仅仅是打印出文本结果而已\n",
    "import sys\n",
    "data.to_csv(sys.stdout, sep='|')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      ",something,a,b,c,d,message\r\n",
      "0,one,1,2,3.0,4,CY\r\n",
      "1,two,5,6,CY,8,world\r\n",
      "2,three,9,10,11.0,12,foo\r\n"
     ]
    }
   ],
   "source": [
    "#（3）\n",
    "#将缺失值NaN替换成其他的值\n",
    "data.to_csv(sys.stdout, na_rep='CY')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "***"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 四、二进制数据格式"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "实现数据的高效二进制格式存储最简单的办法之一是使用Python内置的pickle序列化。pandas对象都有一个用于将数据以pickle格式保存到磁盘上to_pickle方法。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>a</th>\n",
       "      <th>b</th>\n",
       "      <th>c</th>\n",
       "      <th>d</th>\n",
       "      <th>message</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>hello</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>7</td>\n",
       "      <td>8</td>\n",
       "      <td>world</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>9</td>\n",
       "      <td>10</td>\n",
       "      <td>11</td>\n",
       "      <td>12</td>\n",
       "      <td>foo</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   a   b   c   d message\n",
       "0  1   2   3   4   hello\n",
       "1  5   6   7   8   world\n",
       "2  9  10  11  12     foo"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "frame=pd.read_csv('examples/ex1.csv')\n",
    "frame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "#将数据pickle序列化(类似加密)\n",
    "frame.to_pickle('examples/frame_pickle')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>a</th>\n",
       "      <th>b</th>\n",
       "      <th>c</th>\n",
       "      <th>d</th>\n",
       "      <th>message</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "      <td>hello</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>5</td>\n",
       "      <td>6</td>\n",
       "      <td>7</td>\n",
       "      <td>8</td>\n",
       "      <td>world</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>9</td>\n",
       "      <td>10</td>\n",
       "      <td>11</td>\n",
       "      <td>12</td>\n",
       "      <td>foo</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   a   b   c   d message\n",
       "0  1   2   3   4   hello\n",
       "1  5   6   7   8   world\n",
       "2  9  10  11  12     foo"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#通过pickle直接读取被pickle化的数据\n",
    "pd.read_pickle('examples/frame_pickle')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "***"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.5"
  },
  "toc": {
   "base_numbering": 1,
   "nav_menu": {},
   "number_sections": true,
   "sideBar": true,
   "skip_h1_title": false,
   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
   "toc_cell": false,
   "toc_position": {
    "height": "calc(100% - 180px)",
    "left": "10px",
    "top": "150px",
    "width": "282.825px"
   },
   "toc_section_display": true,
   "toc_window_display": true
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
